Students & research opportunities
Join the Multimodal Intelligence Lab (MILab) at UW to develop multimodal AI and world models for perception, prediction, and planning. Our work combines 3D geometry, semantic understanding, and generative modeling, with applications in visual navigation and transportation infrastructure mapping, monitoring, and management.
Graduate opportunities
I primarily recruit Ph.D. and master’s students through UW’s Computer Science & Systems (CSS) programs in the School of Engineering & Technology at UW Tacoma.
MILab students lead research as first authors and build models, datasets, and open-source systems. Recent student achievements include NeurIPS and ICLR oral papers, UW Graduate School Top Scholar Awards, and the Carwein–Andrews Ph.D. Fellowship.
CSS Ph.D. applicants
For doctoral research in multimodal AI, world models, or intelligent transportation, please get in touch before applying to discuss research fit and potential advisor support. The CSS Ph.D. program requires applicants to identify an initial faculty advisor willing to serve.
CSS M.S. applicants
I welcome master’s applicants interested in thesis research or a research project with MILab. This is an opportunity to develop research ideas, build and evaluate AI systems, and prepare for further research in academia or industry.
Research across UW
Master’s & doctoral students in other UW programs
Students in CSE, ECE, and related UW programs can also work with me through research supervision or co-advising. I welcome both prospective and current students interested in master’s thesis research, doctoral research, or research projects.
As a UW Graduate Faculty member with doctoral endorsement, I can also serve on doctoral supervisory committees. I encourage prospective students to apply to the UW graduate program that best fits their academic goals.
Undergraduate research
I welcome undergraduates across UW for research projects, independent study, and design projects. We can identify a starting point based on your interests, preparation, and available time.
Student achievements
Research highlights
Recent work by my Ph.D. students Yifei Dong and Fengyi Wu spans world models, visual navigation, multimodal reasoning, and efficient inference.
- Yifei Dong · World models and navigation
- First author of Language-Conditioned World Modeling for Visual Navigation (NeurIPS 2026 Oral), UniWM (ECCV 2026), and HA-VLN 2.0 (IROS 2026), with Fengyi Wu and collaborators.
- Fengyi Wu · Multimodal reasoning and efficient AI
- First author of GoViG (Findings of ACL 2026), with Yifei Dong and collaborators; coauthor of Lossless Hierarchical Speculative Decoding (ICLR 2026 Oral).
Fellowships & awards
Our students have earned fellowships and conference support from UW and professional societies.
- Two UW Graduate School Top Scholar Awards
- Yifei Dong (2025) and Fengyi Wu (2026), recognized in consecutive years.
- Carwein–Andrews Ph.D. Fellowship
- Yifei Dong (2025), supported by the Vicky L. Carwein and William B. Andrews Endowment for Graduate Programs.
- Conference presentation & travel support
- Yifei Dong (2026):
- UW Graduate School Conference Presentation Award for ECCV.
- IEEE Robotics and Automation Society (RAS) Travel Support for IROS.
- UW Tacoma Council for Campus Engagement Conference and Training Fund award for IROS.
Mentoring outcomes
Research mentorship extends from first projects in high school to graduate study. Selected outcomes among former students and research mentees:
- International science competition awards
- Jasmine Liu earned the ACM Second Award and a Fourth Award in Robotics and Intelligent Machines at Regeneron ISEF 2023. Yulun (Alan) Wu earned a Bronze Prize in Computer Science at the 2020 S.-T. Yau High School Science Award.
- College admissions
- Former high-school mentees have been admitted to MIT, the University of Chicago, the University of Illinois Urbana-Champaign, Imperial College London, and Harvey Mudd College.
Get in touch
Interested in working together? Email zhiqics@uw.edu with a brief introduction and the following:
- Your background: a CV or résumé, plus your current or intended degree program.
- Your research interests: the questions you would like to explore and how they connect with our work. Links to projects, code, or papers are welcome if available.
- Your plans: your intended starting term and the kind of research opportunity you are seeking. Current students can include relevant coursework and the time they can commit to research.
I welcome inquiries about research fit, potential funding, and ways to join MILab through CSS or collaborate from another UW program. A short, thoughtful introduction is a good place to start.